Water Research X最新文献_第4页

Photocatalytic degradation of PFAS under field water matrix conditions using an adsorptive photocatalyst 利用吸附光催化剂在现场水基质条件下光催化降解PFAS

IF 8.2 2区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research X

Pub Date : 2026-01-01 DOI: 10.1016/j.wroa.2026.100485

Yangmo Zhu , Rodney Nelson Leary III , Tianyuan Xu , Ke He , Lee Blaney , Xiaodi Hao , Dongye Zhao

Per- and polyfluoroalkyl substances (PFAS) are ubiquitous in surface waters. While numerous technologies have been investigated to mitigate human exposure, limited information is available for treatment of PFAS in actual field waters. Based on the “concentrate-and-destroy” strategy, we prepared and evaluated an adsorptive photocatalyst, namely gallium-doped activated carbon-supported titanate nanotubes (Ga/TNTs@AC), for treatment of six PFAS in a model surface water. Being most prevalent in the field water, perfluorooctane sulfonate (PFOS) was selected as a representative compound for feasibility and optimization studies. Batch experiments revealed that at a dosage of 1 g/L, Ga/TNTs@AC adsorbed 98% of 100 µg/L PFOS in the surface water within 10 min. Background cations enhanced PFOS removal by suppressing repulsive forces and enabling the cation-bridging effects. Upon UV irradiation, 35.5% of adsorbed PFOS was effectively degraded and 25.8% defluorinated. The photocatalytic defluorination of PFOS was boosted to 70.0% by addition of 60 µM Fe³⁺ during the photodegradation, where formation of Fe³⁺−PFOS and Fe³⁺−DOM complexes reduced the energy barrier, facilitated activation of PFOS, and diminished inhibitory effects of DOM. Acidic conditions were found favorable for both adsorption and photocatalysis of PFOS. Fixed-bed column tests confirmed the effective adsorption of PFOS and other PFAS in the field water, with complete PFOS breakthrough occurred after 5100 bed volumes. Subsequently, the PFAS-laden Ga/TNTs@AC successfully degraded the pre-concentrated PFAS, which also regenerated the Ga/TNTs@AC media for reuse. Ga/TNTs@AC appeared to be a promising material for enabling the “concentrate-&-destroy” strategy for more efficient removal and degradation of PFAS in field waters.

全氟和多氟烷基物质（PFAS）在地表水中普遍存在。虽然已经研究了许多技术来减少人类接触，但在实际现场水域中处理PFAS的信息有限。基于“浓缩-破坏”策略，我们制备并评估了一种吸附光催化剂，即掺镓活性炭负载的钛酸盐纳米管（Ga/TNTs@AC），用于处理模型地表水中的6种PFAS。全氟辛烷磺酸（PFOS）是野外水体中最普遍存在的化合物，本文选择其作为代表化合物进行可行性和优化研究。批量实验表明，在1 g/L的投加量下，Ga/TNTs@AC在10 min内吸附了地表水中98%的100µg/L的PFOS。背景阳离子通过抑制排斥力和实现阳离子桥接效应来增强PFOS的去除。经紫外线照射后，35.5%吸附的全氟辛烷磺酸被有效降解，25.8%被脱氟。在光降解过程中，添加60µM Fe3+可将PFOS的光催化脱氟率提高到70.0%，其中Fe3+−PFOS和Fe3+−DOM络合物的形成降低了能垒，促进了PFOS的活化，减弱了DOM的抑制作用。酸性条件有利于全氟辛烷磺酸的吸附和光催化。固定床柱试验证实了PFOS和其他PFAS在现场水中的有效吸附，在5100层体积后PFOS完全突破。随后，负载PFAS的Ga/TNTs@AC成功地降解了预浓缩的PFAS，并再生了Ga/TNTs@AC介质以供重复使用。Ga/TNTs@AC似乎是一种很有前途的材料，可以实现“浓缩-破坏”策略，更有效地去除和降解现场水中的PFAS。

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引用次数: 0

When population science meets urban sewer networks: Decoding remaining life using life table analytics 当人口科学遇到城市下水道网络：使用生命表分析解码剩余生命

IF 8.2 2区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research X

Pub Date : 2026-01-01 DOI: 10.1016/j.wroa.2025.100467

Jingchao Yang , Tarek Zayed , Dramani Arimiyaw , Mohamed Nashat , Ridwan Taiwo , Ghasan Alfalah , Xianyang Liu , Abdelazim Ibrahim

Global urban sewer infrastructure faces an unprecedented aging crisis, with cascading failures threatening public health, environmental protection, and urban resilience. The American Society of Civil Engineers estimates a $271 billion investment gap for US sewer systems alone, highlighting the urgent need for sewer aging analysis to optimize resource allocation. Current analysis methodologies face a critical implementation barrier: their complex data type requirements limit practical adoption across diverse municipal contexts. This study is inspired by the recognition that sewer pipelines, like human populations, experience age-related deterioration, and the demographic life table can be applied to analyze the dominant factors in this process. The methodology transforms traditional multi-parameter models into a two-input approach requiring only current age and dominant analytical factor, while maintaining statistical rigor through Wilcoxon signed-rank tests with Bonferroni correction. As one of Asia's leading metropolitan centers, Hong Kong presents an ideal case study for sewer aging analysis. Therefore, comprehensive empirical validation was conducted across 148,389 pipeline segments spanning four major regions, 18 districts, six soil types, and diverse environmental conditions, culminating in a quartile-based risk classification system integrated with GIS visualization for immediate spatial risk assessment. This streamlined approach enables immediate implementation using minimal data requirements and facilitates the transition from reactive repair strategies to predictive management approaches. This ease of implementation supports sustainable urban development and resilient sewer systems globally, providing a viable solution to the global infrastructure crisis.

全球城市下水道基础设施面临着前所未有的老化危机，一连串的故障威胁着公共健康、环境保护和城市复原力。美国土木工程师协会估计，仅美国下水道系统就存在2710亿美元的投资缺口，这凸显了对下水道老化分析以优化资源分配的迫切需要。当前的分析方法面临着一个关键的实现障碍：它们复杂的数据类型需求限制了在不同市政环境中的实际采用。这项研究的灵感来自于这样一种认识，即下水道管道就像人口一样，会经历与年龄相关的退化，而人口寿命表可以用来分析这一过程中的主导因素。该方法将传统的多参数模型转化为只需要当前年龄和主导分析因素的双输入方法，同时通过带有Bonferroni校正的Wilcoxon sign -rank检验保持统计严密性。作为亚洲领先的大都市中心之一，香港为下水道老化分析提供了一个理想的研究案例。因此，我们对4个主要区域、18个区、6种土壤类型和不同环境条件下的148,389个管道段进行了全面的实证验证，最终建立了基于四分位数的风险分类系统，并结合GIS可视化进行了即时空间风险评估。这种简化的方法可以使用最小的数据需求立即实现，并促进从被动修复策略到预测管理方法的过渡。这种易于实施的特点支持全球可持续城市发展和弹性下水道系统，为全球基础设施危机提供了可行的解决方案。

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引用次数: 0

An iron-carbon bioretention system for enhancing nitrogen and phosphorus removal: Synergy of vadose and saturated zones 一个铁碳生物保留系统，以提高氮和磷的去除：渗透和饱和区的协同作用

IF 8.2 2区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research X

Pub Date : 2026-01-01 DOI: 10.1016/j.wroa.2026.100486

Jianqiang Zhou , Xiaojuan Wang , Xichen Song , Jiangtao He , Yawen Zhou , Jie Qin , Yifei Xiao , Suxia Gao , Hua Li , Jianlin Liu , Wei Li , Lianbao Cao , Tingting Zhang , Bigui Wei

To enhance the removal of nitrogen and phosphorus pollutants from urban stormwater runoff in bioretention systems, this study developed an iron-carbon bioretention system with a saturated zone. The system's performance in enhanced pollutant removal was systematically investigated, and the synergistic removal mechanisms between the vadose and saturated zones were elucidated. Experimental results demonstrated that the iron-carbon bioretention system achieved high and stable removal efficiencies for dissolved pollutants, with removal rates of 95.97±2.42% for nitrate-nitrogen, 84.63±3.75% for total nitrogen, 94.88±1.92% for total phosphorus, and 86.99±5.57% for COD. These values represent significant improvements of 69.05%, 44.73%, 49.11%, and 18.63%, respectively, compared to a conventional sand-based bioretention system. Mechanistic analysis of nitrogen and phosphorus removal reveals that the system establishes functional zones in the vertical direction. The aerobic environment in the vadose zone facilitated nitrification and the formation of iron oxides, enabling nitrogen transformation and phosphorus adsorption. Conversely, the anaerobic conditions in the saturated zone drove continuous iron-carbon micro-electrolysis, generating Fe²⁺ and [H] as inorganic electron donors. This process promoted autotrophic denitrification and precipitated phosphorus as stable iron phosphate. The iron-carbon also enhanced microbial diversity and enriched functional genera involved in autotrophic denitrification (e.g., Hydrogenophaga, Geobacter) and iron cycling (e.g., Shewanella, Geobacteraceae). Furthermore, the presence of iron oxides suppressed CH₄ production by competing with methanogens for organic substrates. The higher abundances of Desulfobacterota and Bacteroidota contributed to reduced N₂O emissions, thereby mitigating the greenhouse gas footprint of the bioretention system. This study provides a novel strategy for enhancing stormwater purification in bioretention systems.

为了提高生物滞留系统对城市雨水径流中氮磷污染物的去除效果，本研究开发了一种具有饱和带的铁碳生物滞留系统。系统考察了该系统对污染物的强化去除效果，阐明了渗透层与饱和层的协同去除机理。实验结果表明，铁碳生物滞留系统对溶解污染物的去除率高且稳定，对硝酸盐氮的去除率为95.97±2.42%，对总氮的去除率为84.63±3.75%，对总磷的去除率为94.88±1.92%，对COD的去除率为86.99±5.57%。与传统的砂基生物滞留系统相比，这些数值分别提高了69.05%、44.73%、49.11%和18.63%。对脱氮除磷机理分析表明，该体系在垂直方向上形成功能区。气包带的好氧环境有利于硝化作用和氧化铁的形成，有利于氮的转化和磷的吸附。相反，饱和区厌氧条件驱动连续的铁碳微电解，生成Fe2+和[H]作为无机电子供体。这一过程促进了自养反硝化和沉淀磷作为稳定的磷酸铁。铁碳还增强了微生物多样性，并丰富了参与自养反硝化的功能属（例如，Hydrogenophaga, Geobacter）和铁循环（例如，Shewanella, Geobacteraceae）。此外，氧化铁的存在通过与产甲烷菌竞争有机底物抑制了CH4的产生。高丰度的Desulfobacterota和Bacteroidota有助于减少N2O的排放，从而减轻生物滞留系统的温室气体足迹。本研究为加强生物截留系统的雨水净化提供了一种新的策略。

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引用次数: 0

Sorbent- and sorbate-influenced sorption variability and nonlinearity: a meta-analysis on chlorpyrifos with soils, sediments, and other carbonaceous materials 吸附剂和山梨酸影响的吸附变异性和非线性：毒死蜱与土壤、沉积物和其他碳质物质的荟萃分析

IF 8.2 2区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research X

Pub Date : 2026-01-01 DOI: 10.1016/j.wroa.2026.100492

Dave T.F. Kuo, Song-Yan Ho

Inter-sample sorption variability and nonlinearity can ambiguate fate and ecotoxicity assessment of organic pollutants and remediation strategy. Nonlinear sorption models that assume constancy in organic carbon (OC) normalized sorption coefficient (K_OC) are often adopted across different sorbents. This study explored sorbent-side influence on sorption through meta-analysis and modeling of sorption data on chlorpyrifos, a recently Stockholm Convention enlisted non-ionizable organophosphate pesticide, and its main metabolite 3,5,6-trichloropyridinol (TCP). LogK_OC varies by approximately 2 log units among soils and sediments. In predicting sorption with natural geosorbents (n = 519), linear-OC and Freundlich models are outperformed by models considering nonlinear sorbate-side (concentration) and sorbent-side (OC content) effects (

S = K_{O C} f_{O C}^{a} C^{b}

or

K_{O C} f_{O C} ϕ^{a} C^{b}

). All nonlinear chlorpyrifos models are C-linear but f_OC-nonlinear. The resulting models predict fairly against out-of-domain (untrained) sorbents including biosolids, peat, dissolved organic matter (DOM), biochar, vegetative residues, and wood pieces with root mean squared error (RMSE) ranging from 0.17 to 0.72 (n = 304), hinting the possibility of a universal sorption model across different carbonaceous sorbents. These models capture sorbate competition and sorbent configuration, and may apply or adapt to other chemicals and carbonaceous sorbents to accommodate changing sorbent configurations, compositions, or volume/domain accessibility. Metaphysically, the proposed nonlinear models are grounded in a reference-adjustment framework, where overall effects are quantified as adjustments relative to a base-case scenario, as in thermodynamics and kinetics. Overall, results challenge K_OC constancy that underlies most current models while demonstrating the importance of inter-sorbent variations in composition and configuration of organic components for accurate sorption assessment.

样品间的吸附变异性和非线性会影响有机污染物的命运和生态毒性评估以及修复策略。假设有机碳（OC）归一化吸附系数（KOC）恒定的非线性吸附模型常用于不同的吸附剂。本研究通过对最近加入斯德哥尔摩公约的非电离有机磷农药毒死蜱及其主要代谢物3,5,6-三氯吡啶醇（TCP）的吸附数据进行meta分析和建模，探讨了吸附剂侧对吸附的影响。在土壤和沉积物中，LogKOC相差约2个log单位。在预测天然地吸附剂（n = 519）的吸附时，考虑非线性山山酸盐侧（浓度）和吸附剂侧（OC含量）影响的模型（S=KOCfOCaCb或KOCfOCaCb）优于线性OC和Freundlich模型。所有非线性毒死蜱模型均为c -线性，但c -非线性。所得到的模型对包括生物固体、泥炭、溶解有机物（DOM）、生物炭、植物残留物和木片在内的域外（未经训练的）吸附剂进行了相当好的预测，均方根误差（RMSE）范围为0.17至0.72 (n = 304)，这暗示了在不同碳质吸附剂中建立通用吸附模型的可能性。这些模型捕获山梨酸竞争和吸附剂配置，并可适用或适应其他化学品和碳质吸附剂，以适应变化的吸附剂配置，组成，或体积/域可及性。从形而上学上讲，所提出的非线性模型是建立在参考调整框架基础上的，其中整体影响被量化为相对于基本情况的调整，如热力学和动力学。总的来说，结果挑战了当前大多数模型的基础KOC稳定性，同时证明了有机组分组成和配置的吸附剂间变化对准确吸附评估的重要性。

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引用次数: 0

The crucial role of activated sludge models (ASMs) on wastewater treatment processes: Developments, applications, and future perspectives 活性污泥模型（asm）在废水处理过程中的关键作用：发展、应用和未来展望

IF 8.2 2区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research X

Pub Date : 2026-01-01 DOI: 10.1016/j.wroa.2026.100497

Tianlong Zheng , Yuxin Wang , Lin Li , Junxin Liu , Pengyu Li

Activated sludge models (ASMs), the most widely used mathematical models for biological wastewater treatment, offer a simplified matrix-based representation of pollutant biochemical degradation. As understanding of wastewater treatment mechanisms has advanced, the simplifying assumptions of general ASMs have proven unreasonable under certain conditions, prompting their improvement. Existing reviews often focus on the specific application of ASMs, with limited comprehensive analyses of their multi-dimensional extensions and cross-model integrations. This review provides the first systematic overview of the latest developments in ASMs, focusing on model mechanism extension and multi-scale model integration. In terms of mechanism extension, the incorporation of new theories and secondary reaction has enhanced the accuracy of models in simulating membrane bioreactor systems, phosphorus removal, and industrial wastewater treatment. It has also quantified the generation and dissipation pathways of N₂O and provided a basis for sludge reduction and sedimentation control. Regarding model integration, this review focuses on the coupling interfaces between ASMs and other models, such as anaerobic reaction models, convection-diffusion theory, hydrodynamic models, and machine learning. These coupled models enable full-scale simulation from micro-level biochemical reactions to macro-level environmental dynamics. Finally, the review emphasizes that future ASMs developments should focus on improving mechanisms and addressing emerging contaminants. It highlights that integrating artificial intelligence can serve as a key tool to balance model accuracy and parameter identifiability. The present review aims to establish a systematic research framework for ASMs, analyze the limitations of existing models, and ultimately provide insights for enhancing the precision and application of ASMs in wastewater treatment.

活性污泥模型（asm）是废水生物处理中使用最广泛的数学模型，它提供了一种简化的基于矩阵的污染物生化降解表示。随着对废水处理机理的深入了解，一般asm的简化假设在某些条件下被证明是不合理的，这促使了它们的改进。现有的评论通常集中在asm的特定应用上，对其多维扩展和跨模型集成的综合分析有限。本文首次系统综述了asm的最新进展，重点介绍了模型机制扩展和多尺度模型集成。在机理拓展方面，新理论和二次反应的引入提高了模型在模拟膜生物反应器系统、除磷和工业废水处理等方面的准确性。量化了N2O的生成和消散途径，为污泥减量和沉降控制提供了依据。在模型集成方面，本文综述了asm与其他模型的耦合接口，如厌氧反应模型、对流扩散理论、流体动力学模型和机器学习。这些耦合模型使从微观生化反应到宏观环境动力学的全尺寸模拟成为可能。最后，综述强调未来asm的发展应侧重于改进机制和解决新出现的污染物。它强调了集成人工智能可以作为平衡模型准确性和参数可识别性的关键工具。本文旨在建立一个系统的asm研究框架，分析现有模型的局限性，最终为提高asm在废水处理中的精度和应用提供见解。

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引用次数: 0

Using “big data” and non-linear machine learning to infer groundwater contamination mechanisms across a spatially extensive, geologically heterogeneous region 利用“大数据”和非线性机器学习来推断空间广泛、地质异质性区域的地下水污染机制

IF 8.2 2区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research X

Pub Date : 2026-01-01 DOI: 10.1016/j.wroa.2025.100475

Ioan Petculescu , Anna Majury , R. Stephen Brown , Kevin McDermott , Paul Hynds

Groundwater accounts for approximately 98% of available freshwater, with >2 billion people relying on it as a primary drinking water source. Notwithstanding its importance, specific groundwater quality parameters - namely microbial concentrations and non-Escherichia coli coliforms (NEC) - remain understudied. The current study sought to address this gap by modelling three distinct Contamination Indices (CI) corresponding to E. coli concentration, NEC concentration, and the NEC:E. coli concentration ratio. CIs were developed for south Ontario (115,693 km²) using ∼1 million samples from ∼290,000 wells collected between 2010 and 2021. To permit modelling, CIs were linked to 50 subregion-specific variables which impact groundwater quality (e.g., well depth, aquifer type, mean daily precipitation volumes); Generalized Additive Models (GAM) were subsequently developed and associated non-linear partial effects were calculated. Findings suggest NEC concentrations may appropriately indicate a source’s long-term potential for generalized contamination, as the NEC model exhibited high deviance explained (91.9%) due to significant associations (p < 0.05) with factors influencing and/or representing groundwater recharge. A daily summer rainfall “tipping point” was identified, with volumes >3 mm being associated with NEC concentration reductions (p < 0.0001), potentially due to subsoil saturation and/or aquifer contamination dilution. Regions with predominantly deep wells in bedrock aquifers were associated (p < 0.0001) with low NEC:E. coli ratios, i.e., localized contamination mechanisms (e.g., contaminant bypass or short-circuiting) likely dominate in these regions. The presumption that deeper aquifers/wells are “safer” may thus be due for reconsideration. The importance of understanding and inferring contamination mechanisms cannot be overstated, as it serves as a foundation for evidence-based source protection and testing recommendations.

地下水约占可用淡水的98%，有20亿人依赖地下水作为主要饮用水源。尽管它很重要，具体的地下水质量参数- -即微生物浓度和非大肠杆菌大肠菌群- -仍未得到充分研究。目前的研究试图通过模拟三种不同的污染指数（CI）来解决这一差距，这些指数分别对应于大肠杆菌浓度、NEC浓度和NEC:E。大肠杆菌浓度比。ci是在安大略省南部（115,693平方公里）开发的，使用了2010年至2021年间收集的约290,000口井中的约100万份样本。为了建立模型，ci与影响地下水质量的50个分区域特定变量（例如，井深、含水层类型、平均日降水量）相关联；随后建立了广义加性模型（GAM），并计算了相关的非线性局部效应。研究结果表明，NEC浓度可以适当地表明污染源长期潜在的普遍污染，因为NEC模型显示出很高的偏差（91.9%），这是由于影响和/或代表地下水补给的因素显著相关（p < 0.05）。确定了每日夏季降雨量的“临界点”，3毫米的降雨量与NEC浓度降低有关（p < 0.0001），可能是由于地下土壤饱和和/或含水层污染稀释。基岩含水层中以深井为主的区域NEC:E值较低（p < 0.0001）。大肠杆菌比例，即局部污染机制（如污染物旁路或短路）可能在这些地区占主导地位。因此，认为更深的含水层/井更“安全”的假设可能需要重新考虑。理解和推断污染机制的重要性怎么强调都不为过，因为它是基于证据的源保护和检测建议的基础。

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引用次数: 0

Transferable soft-sensors for predicting nitrate in diverse watersheds 用于预测不同流域硝酸盐的可转移软传感器

IF 8.2 2区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research X

Pub Date : 2026-01-01 DOI: 10.1016/j.wroa.2025.100478

Mehran Janmohammadi , Baiqian Shi , Tanveer M. Adyel , David McCarthy

Understanding the spatial and temporal dynamics of nitrates is crucial to mitigate pollution that causes eutrophication and poor aquatic health. However, in-situ sensors for direct nitrate detection are often limited by high costs, frequent maintenance requirements, and low sensitivity. Soft-sensing has emerged as a promising alternative, where nitrates are predicted using surrogate sensors using models or machine learning. This study addresses a central challenge with soft-sensors: their transferability to sites with limited or no training data. We propose a transferable framework that predicts nitrate concentrations using only a small number of training data points together with simple, low-cost sensors such as electrical conductivity, temperature, and turbidity. The approach selects a pre-trained model (PR-TR) from a large model library using only historical surrogate data, with site similarity determined through Euclidean distance and a relative difference metric. For sites with relative differences below 100%, the PR-TR model achieved an average NSE of 0.51 using only 15 data points. For more dissimilar sites, higher data requirements and careful tuning of the learning rate (0.01) were essential, yet PR-TR still outperformed traditional approaches. Compared with artificial neural networks (ANN) and multiple linear regression (MLR), which required >40 data points to reach similar performance, PR-TR delivered robust and efficient predictions using significantly fewer data samples. The model selection process identified suitable PR-TR models capable of achieving positive NSE values even without nitrate data from the validation site. These findings demonstrate that PR-TR offers a practical, data-efficient method for reliable water quality monitoring.

了解硝酸盐的时空动态对减轻污染至关重要，污染会导致富营养化和水生健康状况不佳。然而，用于直接检测硝酸盐的原位传感器往往受到成本高、维护要求频繁和灵敏度低的限制。软测量已经成为一种很有前途的替代方案，其中硝酸盐使用使用模型或机器学习的替代传感器进行预测。本研究解决了软传感器的一个核心挑战：它们在训练数据有限或没有训练数据的场所的可转移性。我们提出了一个可转移的框架，该框架仅使用少量训练数据点以及简单，低成本的传感器（如电导率，温度和浊度）来预测硝酸盐浓度。该方法仅使用历史替代数据从大型模型库中选择预训练模型（PR-TR），通过欧几里得距离和相对差异度量确定站点相似性。对于相对差异低于100%的站点，PR-TR模型仅使用15个数据点就获得了0.51的平均NSE。对于更多不同的站点，更高的数据要求和仔细调整学习率（0.01）是必不可少的，但PR-TR仍然优于传统方法。人工神经网络（ANN）和多元线性回归（MLR）需要40个数据点才能达到相似的性能，与之相比，PR-TR使用更少的数据样本提供了鲁棒和高效的预测。模型选择过程确定了合适的PR-TR模型，即使没有来自验证站点的硝酸盐数据，也能获得正的NSE值。这些发现表明，PR-TR为可靠的水质监测提供了一种实用的、数据高效的方法。

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引用次数: 0

Distribution characteristics, driving factors and risk assessment of nitrate in groundwater of the Yellow River Basin 黄河流域地下水硝酸盐分布特征、驱动因素及风险评价

IF 8.2 2区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research X

Pub Date : 2026-01-01 DOI: 10.1016/j.wroa.2026.100499

Shuangbao Han , Fuyang Huang , Jiaqing Liu , Fucheng Li , Rui An , Rongzhen Xu , Yan Zheng , Shengpin Li , Wenpeng Li

Nitrogen fertilizers are widely used in agricultural production, and their residues can migrate to aquifers, threatening groundwater safety. As an important region for agricultural and energy production in China, the Yellow River Basin has seen the long-term application of nitrogen fertilizers. In this study, Based on the nitrate (NO₃⁻-N) data from 3116 groundwater monitoring sites collected over 2018–2022, this study investigated the occurrence and distribution characteristics of NO₃⁻-N in groundwater. Specifically, the driving factors of the migration and occurrence of NO₃⁻-N in groundwater were identified. The results show that the average concentration of NO₃⁻-N is 9.04 mg/L in the monitoring sites, and the rate of concentration exceed 10 mg/L is 24.71%. The average concentration of NO₃⁻-N gradually increases from the upstream to the downstream. The average concentration of NO₃⁻-N in groundwater decreases significantly with increasing depth, decreased from 5.75 mg/L (depth: 0–50 m) to 1.8 mg/L (depth: ≥200 m). The concentration of NO₃⁻-N in phreatic water is notably higher than that in confined water. High-concentrations of NO₃⁻-N (>10 mg/L) are mainly distributed in the areas with developed agriculture and industry. Especially in the areas of phreatic aquifers with suitable temperature, abundant rainfall, intensive industrial and agricultural activities, an oxidizing, Na-Cl and Ca-Mg-Cl type groundwater environment. In some monitoring sites of phreatic aquifers with depths <50 m, NO₃⁻-N pose risks to human health.

氮肥在农业生产中广泛使用，其残留物会迁移到含水层，威胁地下水安全。黄河流域作为中国重要的农业和能源产区，氮肥的长期施用。在这项研究中，基于2018-2022年3116个地下水监测点的硝酸盐（NO₃⁻-N）数据，研究了NO₃⁻-N在地下水中的发生和分布特征。具体来说，确定了地下水中NO₃⁻-N迁移和发生的驱动因素。结果表明，监测点NO₃⁻-N的平均浓度为9.04 mg/L，浓度超过10 mg/L的比例为24.71%。NO₃-N的平均浓度从上游到下游逐渐增加。地下水中NO₃⁻-N的平均浓度随着深度的增加而显著降低，从5.75 mg/L（深度0-50 m）下降到1.8 mg/L（深度≥200 m）。NO₃-N在潜水中的浓度明显高于承压水中的浓度。高浓度的NO₃⁻-N（10毫克/升）主要分布在农业和工业发达的地区。特别是在温度适宜、雨量充沛、工农业活动密集、具有氧化性、Na-Cl和Ca-Mg-Cl型地下水环境的潜水含水层地区。在一些深度为50米的潜水含水层监测点，NO₃⁻-N对人类健康构成威胁。

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引用次数: 0

Methane emissions monitoring at wastewater treatment plants in Europe and Australia 欧洲和澳大利亚污水处理厂的甲烷排放监测

IF 8.2 2区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research X

Pub Date : 2026-01-01 DOI: 10.1016/j.wroa.2025.100480

P de Jong , B Srinamasivayam , A Harrison , P Wardrop , M Rebsdorf , S Thorgaard , P Vale

Methane (CH₄) emissions from wastewater treatment plants (WWTPs) represent a significant greenhouse gas (GHG) source, challenging utilities aiming for net-zero carbon goals. The majority of the non-biogenic, direct (Scope 1) wastewater treatment plant emissions originate from i) nitrous oxide from the secondary wastewater treatment, and ii) CH₄ from the anaerobic degradation of wastewater and wastewater sludge. This study evaluates the effectiveness and suitability of various emissions measurement technologies and methodologies for quantifying methane emissions from wastewater treatment processes using data from monitoring trials conducted across treatment plants in Europe and Australia. The results provide a practical framework to guide utilities in selecting the most appropriate methods for monitoring and quantifying fugitive methane emissions from key sources such as open sludge storage, digesters, and sludge drying pans. . Findings across the 3 utilities indicate CH₄ losses of 5 %–25 % of total CH₄ production, with legacy assets like floating roof digesters contributing 245–2200 tCO₂e/year. At Melbourne Water’s Eastern Treatment Plant (ETP), measurement campaigns found that the open sludge drying pans were a major source of emissions and a mobile survey mapping campaign measured site-wide emissions of 46,000–114,000 tCO₂e/year. Aarhus Vand’s Egå WWTP measured CH₄ losses at ∼7 % of total CH₄ production, predominantly from vented sludge storage tanks. The study reviews advanced CH₄ measurement technologies, analysing emissions from WWTPs with sludge treatment centres. Normalised emissions key performance indicators are proposed, with discussions on limitations and mitigation strategies. Recommendations include tailored measurement methods, immediate leak detection and repair, and long-term investments in asset upgrades and alternative sludge treatment technologies.

污水处理厂（WWTPs）的甲烷（CH₄）排放是一个重要的温室气体（GHG）来源，对旨在实现净零碳目标的公用事业公司构成了挑战。大多数非生物源性的直接（范围1）废水处理厂的排放来自i)二级废水处理产生的氧化亚氮，以及ii)废水和废水污泥厌氧降解产生的甲烷。本研究评估了各种排放测量技术和方法的有效性和适用性，这些技术和方法用于量化废水处理过程中的甲烷排放，使用的数据来自欧洲和澳大利亚的处理厂进行的监测试验。结果提供了一个实用的框架，以指导公用事业公司选择最合适的方法来监测和量化主要来源的逸散性甲烷排放，如开放式污泥储存，消化器和污泥干燥盘。三家公用事业公司的调查结果表明，CH4损失占CH4总产量的5% - 25%，浮动屋顶沼气池等遗留资产每年贡献245-2200 tCO₂e。在墨尔本水务的东部处理厂（ETP），测量活动发现开放式污泥干燥盘是排放的主要来源，移动调查测绘活动测量了整个站点的排放量为46,000-114,000 tCO₂e/年。Aarhus Vand的eg污水处理厂测量的CH4损失占总CH4产量的约7%，主要来自通风污泥储存罐。该研究回顾了先进的甲烷测量技术，分析了污水处理厂与污泥处理中心的排放。提出了标准化排放关键绩效指标，并讨论了限制和缓解战略。建议包括量身定制的测量方法，即时泄漏检测和修复，以及对资产升级和替代污泥处理技术的长期投资。

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引用次数: 0

Phytoplankton community assembly and health assessment in the middle-lower Jialing River via high-throughput sequencing 基于高通量测序的嘉陵江中下游浮游植物群落组合与健康评价

IF 8.2 2区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research X

Pub Date : 2025-12-14 DOI: 10.1016/j.wroa.2025.100470

Yuelin Tang , Fei Xu , Qingyun Yang , Tuo Zhang

This study evaluates the aquatic ecosystem health of the Jialing River (Nanchong section), a key Yangtze tributary, through phytoplankton-based assessment, providing scientific support for its ecological conservation and rehabilitation. In May 2023, phytoplankton samples from 22 sites in the Jialing River system were analyzed via high-throughput sequencing. Multivariate analyses (Spearman/NMDS/RDA/SEM) revealed diversity patterns and drivers, enabling ecological quality assessment of the mainstem and Xichong River tributary. Community assembly mechanisms were further elucidated. Results: (1) Phytoplankton composition analysis revealed 341 species from 196 genera and 7 phyla in the Jialing River system. Bacillariophyta, Chlorophyta, and Cyanophyta were dominant phyla. The mainstem was dominated by Synechococcus and Chlorella, while Synechococcus, Aulacoseira, Cyclotella, and Gomphosphaeria were predominant in the Xichong River tributary. (2) Significant differences (P < 0.05) in phytoplankton community structure and diversity were observed between the Jialing mainstem and Xichong River, with permanganate index (CODMn) and total phosphorus (TP) identified as key influencing factors. (3) The P-IBI assessment classified the mainstem as "healthy" and the Xichong River as "moderate" in ecological status. P-IBI showed significant correlations (P < 0.05) with TP, CODMn, NH₃-N, and diversity indices (Simpson, Pielou, Shannon). (4) Stochastic processes dominated phytoplankton community assembly, indicating relatively good ecosystem health. Overall, the mid-lower mainstem exhibited better ecological conditions than tributaries, though poor tributary health remains a potential risk to the entire watershed.

通过基于浮游植物的评价方法，对长江重点支流嘉陵江南充段的水生生态系统健康状况进行了评价，为嘉陵江南充段的生态保护与修复提供了科学依据。2023年5月，对嘉陵江水系22个样点的浮游植物样品进行了高通量测序分析。多变量分析（Spearman/NMDS/RDA/SEM）揭示了西充江干流和支流生态质量的多样性格局和驱动因素。进一步阐明了社区集会机制。结果：(1)嘉陵江水系浮游植物组成分析结果显示，嘉陵江水系浮游植物共有7门196属341种。硅藻门、绿藻门和蓝藻门为优势门。西冲河支流以聚球菌和小球藻为主，以聚球菌、Aulacoseira、Cyclotella和Gomphosphaeria为主。(2)嘉陵干流与西冲河浮游植物群落结构和多样性存在显著差异（P < 0.05），高锰酸盐指数（CODMn）和总磷（TP）是主要影响因子。(3) P-IBI评价将西冲河的生态状况划分为“健康”和“中等”。P- ibi与TP、CODMn、NH3-N和多样性指数呈显著相关（P < 0.05）（Simpson, Pielou, Shannon）。(4)浮游植物群落组成以随机过程为主，生态系统健康状况较好。总体而言，中下游干流的生态条件好于支流，但支流健康状况不佳仍对整个流域构成潜在风险。

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引用次数: 0